Openclaw Skills helps you decide whether a workflow is suitable for an AI agent and returns practical, best-practice design recommendations.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install agent-design-advisor
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install agent-design-advisor using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Agent Design Advisor?
Openclaw Skills for Agent Design Advisor is a decision-making skill that evaluates a described workflow against agent suitability criteria and then produces actionable architecture guidance. It is designed for situations where you want to know whether an AI agent is the right implementation choice before investing in design or tooling.
The skill does not generate code or provide a full system review. Instead, it focuses on high-signal evaluation: identifying whether the workflow contains complex decisions, hard-to-maintain rules, or unstructured data dependencies, then translating that assessment into clear recommendations for model capability, tool boundaries, instruction design, orchestration pattern, and guardrails.
Agent Design Advisor Use Cases
- Assessing whether a business workflow should be implemented with an AI agent or a deterministic approach
- Reviewing workflows with nuanced decisions, exception handling, or context-sensitive actions
- Evaluating rule-heavy processes that are costly to maintain or prone to errors
- Handling workflows that require natural language understanding, document interpretation, or conversational interaction
- Designing agent-based systems for tasks like approvals, reviews, extraction, and decision support
- Planning safety, moderation, and output validation for agent deployments
- Starting with a single-agent design and determining when multi-agent orchestration is actually warranted
How Agent Design Advisor Works
- The user provides a workflow description and asks whether it is suitable for AI agent implementation.
- The skill evaluates the workflow against three required criteria: complex decision-making, difficult-to-maintain rules, and unstructured data dependency.
- If at least one criterion is met, the workflow is classified as suitable; if none are met, it is classified as not suitable.
- When suitable, the skill generates design advice across five modules: model selection, tool definition, instruction configuration, orchestration pattern, and guardrail configuration.
- The recommendations follow a progressive deployment mindset: start with privacy and content safety, then expand using real examples, and finally optimize iteratively.
- The skill outputs a structured conclusion that summarizes the judgment, evidence, and practical next steps.
Agent Design Advisor Setup
This skill is designed for use as a guided evaluation workflow rather than a software package, so there is no runtime installation or SDK setup.
- Provide a clear workflow description, including goals, inputs, outputs, edge cases, and any external systems involved.
- Ask whether the workflow is suitable for AI agent implementation.
- Ensure the description includes enough context for the three evaluation criteria to be assessed.
- If you are integrating this into an Openclaw Skills environment, make sure the skill is available in your agent skill registry or prompt-routing configuration.
- Use the resulting recommendation to define a phased implementation plan before building any agent logic.
# No installation commands are required for this skill
# Use it by supplying a workflow description to the agent
For best results, document the workflow boundaries, existing rule systems, and any data privacy or moderation constraints before invoking Openclaw Skills.
Agent Design Advisor Data Schema & Taxonomy
This skill does not generate a persistent data model, but it does produce a structured advisory output with a consistent evaluation taxonomy.
Input structure
| Field | Purpose |
|---|---|
| Workflow description | The process to evaluate |
| Decision complexity | Signals for nuanced judgment or exception handling |
| Rule maintainability | Signals for rule sprawl, brittleness, or high update cost |
| Unstructured data dependence | Signals for natural language, documents, or conversation |
Evaluation taxonomy
- Complex decision-making: nuanced judgment, exceptions, or context-sensitive choices
- Hard-to-maintain rules: bloated, brittle, or frequently changing rule systems
- Unstructured data dependency: natural language understanding, document extraction, or dialogue
Output structure
| Section | Contents |
|---|---|
| 评估结论 | Suitable / not suitable judgment |
| 依据 | Criteria matched and workflow characteristics |
| 设计建议 | Model selection, tools, instructions, orchestration, guardrails |
| 注意事项 | Scope limits and rollout guidance |
Guardrail taxonomy
- Relevance classification
- Security classification
- PII filtering
- Moderation
- Tool safety protection
- Rule protection
- Output validation
Agent Design Advisor Advanced Features
- Supports a strict two-stage advisory flow: suitability assessment first, then design recommendations only when the workflow qualifies
- Uses a criteria-based decision framework grounded in OpenAI's "A Practical Guide to Building Agents"
- Encourages progressive deployment, starting with minimal scope and expanding after real-user validation
- Recommends agent architecture without binding to a specific model family or SDK implementation
- Helps teams compare single-agent and multi-agent patterns before committing to orchestration complexity
- Includes a guardrail strategy covering relevance, safety, PII filtering, moderation, tool protection, rule protection, and output validation
- Designed for Openclaw Skills workflows that need high-signal evaluation without code generation
SKILL.md
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